PyTorch implementation of UNet++ (Nested U-Net).

Related tags

Deep Learningpytorchimage-segmentationunet
Overview

PyTorch implementation of UNet++ (Nested U-Net)

MIT License

This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architecture for Medical Image Segmentation implemented in PyTorch.

[NEW] Add support for multi-class segmentation dataset.

[NEW] Add support for PyTorch 1.x.

Requirements

  • PyTorch 1.x or 0.41

Installation

  1. Create an anaconda environment.
conda create -n=<env_name> python=3.6 anaconda
conda activate <env_name>
  1. Install PyTorch.
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
  1. Install pip packages.
pip install -r requirements.txt

Training on 2018 Data Science Bowl dataset

  1. Download dataset from here to inputs/ and unzip. The file structure is the following:
inputs
└── data-science-bowl-2018
    ├── stage1_train
    |   ├── 00ae65...
    │   │   ├── images
    │   │   │   └── 00ae65...
    │   │   └── masks
    │   │       └── 00ae65...            
    │   ├── ...
    |
    ...
  1. Preprocess.
python preprocess_dsb2018.py
  1. Train the model.
python train.py --dataset dsb2018_96 --arch NestedUNet
  1. Evaluate.
python val.py --name dsb2018_96_NestedUNet_woDS

(Optional) Using LovaszHingeLoss

  1. Clone LovaszSoftmax from bermanmaxim/LovaszSoftmax.
git clone https://github.com/bermanmaxim/LovaszSoftmax.git
  1. Train the model with LovaszHingeLoss.
python train.py --dataset dsb2018_96 --arch NestedUNet --loss LovaszHingeLoss

Training on original dataset

Make sure to put the files as the following structure (e.g. the number of classes is 2):

inputs
└── <dataset name>
    ├── images
    |   ├── 0a7e06.jpg
    │   ├── 0aab0a.jpg
    │   ├── 0b1761.jpg
    │   ├── ...
    |
    └── masks
        ├── 0
        |   ├── 0a7e06.png
        |   ├── 0aab0a.png
        |   ├── 0b1761.png
        |   ├── ...
        |
        └── 1
            ├── 0a7e06.png
            ├── 0aab0a.png
            ├── 0b1761.png
            ├── ...
  1. Train the model.
python train.py --dataset <dataset name> --arch NestedUNet --img_ext .jpg --mask_ext .png
  1. Evaluate.
python val.py --name <dataset name>_NestedUNet_woDS

Results

DSB2018 (96x96)

Here is the results on DSB2018 dataset (96x96) with LovaszHingeLoss.

Model IoU Loss
U-Net 0.839 0.365
Nested U-Net 0.842 0.354
Nested U-Net w/ Deepsupervision 0.843 0.362
Owner
4ui_iurz1
4ui_iurz1
GitHub Repository
Reading list for research topics in Masked Image Modeling

awesome-MIM Reading list for research topics in Masked Image Modeling(MIM). We list the most popular methods for MIM, if I missed something, please su

ligang 231 Dec 07, 2022
Code for "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" paper

UNICORN 🦄 Webpage | Paper | BibTex PyTorch implementation of "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" pap

118 Jan 06, 2023
Online Multi-Granularity Distillation for GAN Compression (ICCV2021)

Online Multi-Granularity Distillation for GAN Compression (ICCV2021) This repository contains the pytorch codes and trained models described in the IC

Bytedance Inc. 299 Dec 16, 2022
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation Official PyTorch Implementation

: We present a novel, real-time, semantic segmentation network in which the encoder both encodes and generates the parameters (weights) of the decoder. Furthermore, to allow maximal adaptivity, the w

Yuval Nirkin 182 Dec 14, 2022
Learning with Noisy Labels via Sparse Regularization, ICCV2021

Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari

Xiong Zhou 38 Oct 20, 2022
Facial expression detector

A tensorflow convolutional neural network model to detect facial expressions.

Carlos Tardón Rubio 5 Apr 20, 2022
A Python module for parallel optimization of expensive black-box functions

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Paul Knysh 426 Dec 08, 2022
Official code for "On the Frequency Bias of Generative Models", NeurIPS 2021

Frequency Bias of Generative Models Generator Testbed Discriminator Testbed This repository contains official code for the paper On the Frequency Bias

35 Nov 01, 2022
Code for the paper "Asymptotics of ℓ2 Regularized Network Embeddings"

README Code for the paper Asymptotics of L2 Regularized Network Embeddings. Requirements Requires Stellargraph 1.2.1, Tensorflow 2.6.0, scikit-learm 0

Andrew Davison 0 Jan 06, 2022
Modeling CNN layers activity with Gaussian mixture model

GMM-CNN This code package implements the modeling of CNN layers activity with Gaussian mixture model and Inference Graphs visualization technique from

3 Aug 05, 2022
Benchmark library for high-dimensional HPO of black-box models based on Weighted Lasso regression

LassoBench LassoBench is a library for high-dimensional hyperparameter optimization benchmarks based on Weighted Lasso regression. Note: LassoBench is

Kenan Šehić 5 Mar 15, 2022
Automatic labeling, conversion of different data set formats, sample size statistics, model cascade

Simple Gadget Collection for Object Detection Tasks Automatic image annotation Conversion between different annotation formats Obtain statistical info

llt 4 Aug 24, 2022
Data and Code for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning"

Introduction Code and data for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning". We cons

Pan Lu 81 Dec 27, 2022
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th

Daniel Stanley Tan 325 Dec 28, 2022
ADGAN - The Implementation of paper Controllable Person Image Synthesis with Attribute-Decomposed GAN

ADGAN - The Implementation of paper Controllable Person Image Synthesis with Attribute-Decomposed GAN CVPR 2020 (Oral); Pose and Appearance Attributes Transfer;

Men Yifang 400 Dec 29, 2022
Wordle-solver - Wordle answer generation program in python

🟨 Wordle Solver 🟩 Wordle answer generation program in python ✔️ Requirements U

Dahyun Kang 4 May 28, 2022
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Cuong Nguyen 1 Jan 18, 2022
A pytorch-based real-time segmentation model for autonomous driving

CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap

342 Dec 22, 2022
Implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".

PRP Introduction This is the implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".

yuanyao366 39 Dec 29, 2022
FedScale: Benchmarking Model and System Performance of Federated Learning

FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca

268 Jan 01, 2023